{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0.0-alpha0\n",
      "GPU Available:  True\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pathlib import Path\n",
    "import glob\n",
    "import pickle\n",
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "from lstm import LSTM_Simple\n",
    "from metrics import exact_match_metric\n",
    "from callbacks import NValidationSetsCallback, GradientLogger\n",
    "from generator import DataGenerator, DataGeneratorSeq\n",
    "from tqdm import tqdm\n",
    "from evaluate_lstm import LSTM_Evaluator\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "print(tf.__version__)\n",
    "print(\"GPU Available: \", tf.test.is_gpu_available())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helper Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_two_results(result_1, result_2=None, experiments=['L&L'], title=''):\n",
    "    labels = []\n",
    "    array_1 = []\n",
    "    array_2 = []\n",
    "    \n",
    "    for module in result_1:\n",
    "        labels.append(module.split('__')[1])\n",
    "        array_1.append(result_1[module])\n",
    "\n",
    "    if result_2 is not None:\n",
    "        for module in result_1:\n",
    "            array_2.append(result_2[module])\n",
    "\n",
    "    x = np.arange(len(labels))  # the label locations\n",
    "    width = 0.35  # the width of the bars\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    if result_2 is not None:\n",
    "        rects1 = ax.bar(x - width/2, array_1, width, label=experiments[0])\n",
    "        rects2 = ax.bar(x + width/2, array_2, width, label=experiments[1])\n",
    "    else:\n",
    "        rects1 = ax.bar(x, array_1, width, label=experiments[0])\n",
    "\n",
    "\n",
    "    # Add some text for labels, title and custom x-axis tick labels, etc.\n",
    "    ax.set_ylabel('Scores')\n",
    "    ax.set_title('Evaluation scores: ' + title)\n",
    "    ax.set_xticks(x)\n",
    "    ax.set_xticklabels(labels, rotation=30, ha=\"right\")\n",
    "    ax.legend()\n",
    "\n",
    "\n",
    "    def autolabel(rects):\n",
    "        \"\"\"Attach a text label above each bar in *rects*, displaying its height.\"\"\"\n",
    "        for rect in rects:\n",
    "            height = rect.get_height()\n",
    "            ax.annotate('{0:.2f}'.format(height),\n",
    "                        xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                        xytext=(0, 3),  # 3 points vertical offset\n",
    "                        textcoords=\"offset points\",\n",
    "                        ha='center', va='bottom')\n",
    "\n",
    "\n",
    "    if result_2 is not None:\n",
    "        autolabel(rects2)\n",
    "\n",
    "    autolabel(rects1)\n",
    "\n",
    "    fig.tight_layout()\n",
    "    plt.ylim([0, 1.1])\n",
    "    plt.legend(loc='lower right')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "def concatenate_texts_individual(path, pattern):\n",
    "    file_paths = list(path.glob('{}*.txt'.format(pattern)))\n",
    "    \n",
    "    input_texts = {}\n",
    "    target_texts = {}\n",
    "\n",
    "    for file_path in file_paths:\n",
    "        if file_path.stem not in input_texts:\n",
    "            input_texts[file_path.stem] = []\n",
    "            target_texts[file_path.stem] = []\n",
    "        \n",
    "        with open(str(file_path), 'r', encoding='utf-8') as f:\n",
    "            lines = f.read().split('\\n')[:-1]\n",
    "\n",
    "        input_texts[file_path.stem].extend(lines[0::2])\n",
    "        target_texts[file_path.stem].extend(['\\t' + target_text + '\\n' for target_text in lines[1::2]])\n",
    "        \n",
    "    return input_texts, target_texts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_data(settings_path):\n",
    "    with open(str(settings_path), 'r') as file:\n",
    "        settings_dict = json.load(file)\n",
    "\n",
    "    raw_path = Path(settings_dict['data_path'])\n",
    "    interpolate_path = raw_path/'interpolate'\n",
    "    extrapolate_path = raw_path/'extrapolate'\n",
    "    train_easy_path = raw_path/'train-easy/'\n",
    "    \n",
    "    \n",
    "    math_module = settings_dict[\"math_module\"]\n",
    "    train_level = settings_dict[\"train_level\"]\n",
    "\n",
    "    datasets = {\n",
    "        'train':(raw_path, 'train-' + train_level + '/' + math_module),\n",
    "        'interpolate':(interpolate_path, math_module),\n",
    "        'extrapolate':(extrapolate_path, math_module)\n",
    "               }\n",
    "\n",
    "    input_texts = {}\n",
    "    target_texts = {}\n",
    "\n",
    "    for k, v in datasets.items():\n",
    "        input_texts[k], target_texts[k] = concatenate_texts_individual(v[0], v[1])\n",
    "    \n",
    "    return settings_dict, input_texts, target_texts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate_arithmetics_interpolate(lstm_eval, input_texts, target_texts, print_res=False):\n",
    "    test_set = 'interpolate'\n",
    "    results = {}\n",
    "\n",
    "    results_deepmind = {'arithmetic__add_or_sub': 0.875,\n",
    "                        'arithmetic__add_or_sub_in_base': 0.9,\n",
    "                        'arithmetic__add_sub_multiple': .95,\n",
    "                        'arithmetic__mul_div_multiple': .95,\n",
    "                        'arithmetic__nearest_integer_root': .875,\n",
    "                        'arithmetic__mul': 0.45,\n",
    "                        'arithmetic__div': 0.78,\n",
    "                        'arithmetic__simplify_surd':0.16,\n",
    "                        'arithmetic__mixed': 0.62}\n",
    "\n",
    "    for module in input_texts[test_set]:\n",
    "        metric = lstm_eval.evaluate_model(input_texts[test_set][module], target_texts[test_set][module])\n",
    "        if print_res:\n",
    "            print(test_set, module)\n",
    "            print('metric:', metric, '\\n')        \n",
    "        results[module] = metric\n",
    "\n",
    "    plot_two_results(results, results_deepmind, experiments=['L&L', 'DM'], title='interpolation')\n",
    "    \n",
    "    return results, results_deepmind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate_arithmetics_extrapolate(lstm_eval, input_texts, target_texts, print_res=False):\n",
    "    test_set = 'extrapolate'\n",
    "    results = {}\n",
    "\n",
    "    results_deepmind = {'arithmetic__add_or_sub_big': 0.3,\n",
    "                        'arithmetic__add_sub_multiple_longer': 0.55,\n",
    "                        'arithmetic__mul_big': .225,\n",
    "                        'arithmetic__mixed_longer': 0.1,\n",
    "                        'arithmetic__mul_div_multiple_longer': 0.55,\n",
    "                        'arithmetic__div_big':0.625}\n",
    "\n",
    "    for module in input_texts[test_set]:\n",
    "        \n",
    "        metric = lstm_eval.evaluate_model(input_texts[test_set][module], target_texts[test_set][module])\n",
    "        if print_res:\n",
    "            print(test_set, module)\n",
    "            print('metric:', metric, '\\n')\n",
    "        results[module] = metric\n",
    "\n",
    "    plot_two_results(results, results_deepmind, experiments=['L&L', 'DM'], title='extrapolation')\n",
    "    return results, results_deepmind"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_ids = {1:'j4bu146wamlr9', 2: 'js0kldpwp1nhos', 3: 'jroi3ag4aros6'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 j4bu146wamlr9\n",
      "2 js0kldpwp1nhos\n",
      "3 jroi3ag4aros6\n"
     ]
    }
   ],
   "source": [
    "for key, value in job_ids.items():\n",
    "    print(key, value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_path = Path('../../../storage/artifacts/'  + job_ids[1])\n",
    "settings_dict, input_texts, target_texts = get_data(model_path/'settings.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluate datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EPOCH 1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EPOCH 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EPOCH 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for epoch, job_id in job_ids.items():\n",
    "    model_path = Path('../../../storage/artifacts/'  + job_id)\n",
    "    lstm_eval = LSTM_Evaluator(model_path)\n",
    "    print('EPOCH', epoch)\n",
    "    res, res_dm = evaluate_arithmetics_interpolate(lstm_eval, input_texts, target_texts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EPOCH 1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EPOCH 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EPOCH 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for epoch, job_id in job_ids.items():\n",
    "    model_path = Path('../../../storage/artifacts/'  + job_id)\n",
    "    lstm_eval = LSTM_Evaluator(model_path)\n",
    "    print('EPOCH', epoch)\n",
    "    res, res_dm = evaluate_arithmetics_extrapolate(lstm_eval, input_texts, target_texts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## We can also test an indiviual string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'-4'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lstm_eval.predict_on_string('1 / 7')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lstm_eval.predict_on_string('2*2')"
   ]
  }
 ],
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